Same principle, but different computations in representing time and space.

Area of Science:

• Cognitive Neuroscience
• Psychology
• Sensory Perception

Background:

• Time and space are fundamental to human cognition and are theorized to share common processing mechanisms, as proposed by the "A Theory of Magnitude" (ATOM).
• Existing evidence on shared computational mechanisms for time and space perception is mixed, necessitating further investigation.

Purpose of the Study:

• To investigate the shared and distinct computational properties underlying human time and space perception.
• To compare the application of observer models, specifically Bayesian computations, to time and distance interval reproduction.

Main Methods:

• Human subjects were tasked with reproducing time and distance intervals using saccadic eye movements in controlled experimental designs.
• Observer models were applied to analyze the data from both time and distance reproduction tasks to assess computational properties.
• Measurement and motor variability were quantified for both temporal and spatial reproductions.

Main Results:

• Both time and space computations were found to be probabilistic, but Bayesian computations significantly improved the model for time perception, with minimal impact on space perception.
• Motor variability, associated with saccadic eye movements, was correlated between time and distance reproduction tasks.
• Measurement and motor variability were lower for distance reproduction compared to time reproduction.

Conclusions:

• Time and space perception appear to operate under a shared fundamental algorithm but exhibit distinct computational characteristics.
• The findings suggest that while the underlying mechanism is similar, the specific implementation and reliance on Bayesian inference differ between time and space processing.